A Vanilla LSTM is an LSTM model that has a single hidden layer of LSTM units. The encoder is responsible for interpreting and reading the input sequence whereas the output encoder has a fixed-length vector[1]}. Vanilla LSTM has a property to isolate the effect due to change on the performance variant. So, when vanilla LSTM is used as a baseline it evaluates with all of its variants and allows the isolating effect for the changes made in each of the variants. The performance of vanilla LSTM is reasonably well on various data sets[2]}. This vanilla LSTM is kind of art model for different variety of machine learning programs. So, vanilla LSTM neural networks predict with accuracy making most of the long short-term memory when the cases are complicated while operating[3]}.
